Spatial displacement vector prediction for intra picture block and string copying

ABSTRACT

A method, computer program, and computer system is provided for coding video data. Video data including one or more blocks is received. A current block coded in intra block copy mode or string matching mode is predicted from among the one or more blocks based on a coded block vector or a string offset vector corresponding to one or more spatial neighboring or non-neighboring blocks from among the one or more blocks. The video data is decoded based on the predicted current block.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority based on U.S. Provisional ApplicationNo. 63/038,020 (filed Jun. 11, 2020), the entirety of which isincorporated by reference herein.

FIELD

This disclosure relates generally to field of data processing, and moreparticularly to video encoding and decoding.

BACKGROUND

Block based compensation from a different picture is also known asmotion compensation. Similarly, a block compensation can also be donefrom a previously reconstructed area within the same picture. This isreferred as intra picture block compensation, current picturereferencing (CPR for short), or intra block copy (IBC for short).

SUMMARY

Embodiments relate to a method, system, and computer readable medium forvideo coding. According to one aspect, a method for video coding isprovided. The method may include receiving video data including one ormore blocks. A current block coded in intra block copy mode is predictedfrom among the one or more blocks based on a coded block vector orstring offset vector corresponding to one or more spatial neighboring ornon-neighboring blocks from among the one or more blocks. The video datais decoded based on the predicted current block.

According to another aspect, a computer system for video coding isprovided. The computer system may include one or more processors, one ormore computer-readable memories, one or more computer-readable tangiblestorage devices, and program instructions stored on at least one of theone or more storage devices for execution by at least one of the one ormore processors via at least one of the one or more memories, wherebythe computer system is capable of performing a method. The method mayinclude receiving video data including one or more blocks. A currentblock coded in intra block copy mode is predicted from among the one ormore blocks based on a coded block vector or string offset vectorcorresponding to one or more spatial neighboring or non-neighboringblocks from among the one or more blocks. The video data is decodedbased on the predicted current block.

According to yet another aspect, a computer readable medium for videocoding is provided. The computer readable medium may include one or morecomputer-readable storage devices and program instructions stored on atleast one of the one or more tangible storage devices, the programinstructions executable by a processor. The program instructions areexecutable by a processor for performing a method that may accordinglyinclude receiving video data including one or more blocks. A currentblock coded in intra block copy mode is predicted from among the one ormore blocks based on a coded block vector or string offset vectorcorresponding to one or more spatial neighboring or non-neighboringblocks from among the one or more blocks. The video data is decodedbased on the predicted current block.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects, features and advantages will become apparentfrom the following detailed description of illustrative embodiments,which is to be read in connection with the accompanying drawings. Thevarious features of the drawings are not to scale as the illustrationsare for clarity in facilitating the understanding of one skilled in theart in conjunction with the detailed description. In the drawings:

FIG. 1 illustrates a networked computer environment according to atleast one embodiment;

FIG. 2A is a block diagram depicting intra block copy in a picture,according to at least one embodiment;

FIG. 2B is a block diagram of intra block compensation with a one codingtree unit (CTU) search range, according to at least one embodiment;

FIG. 2C is a block diagram of HEVC/VVC spatial merge candidates,according to at least one embodiment;

FIG. 2D is a block diagram of spatial blocks, according to at least oneembodiment;

FIG. 3 is an operational flowchart illustrating the steps carried out bya program that encodes and decodes video data based on spatialdisplacement vectors, according to at least one embodiment;

FIG. 4 is a block diagram of internal and external components ofcomputers and servers depicted in FIG. 1 according to at least oneembodiment;

FIG. 5 is a block diagram of an illustrative cloud computing environmentincluding the computer system depicted in FIG. 1, according to at leastone embodiment; and

FIG. 6 is a block diagram of functional layers of the illustrative cloudcomputing environment of FIG. 5, according to at least one embodiment.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. Those structures and methods may, however, beembodied in many different forms and should not be construed as limitedto the exemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope to those skilled in the art. Inthe description, details of well-known features and techniques may beomitted to avoid unnecessarily obscuring the presented embodiments.

Embodiments relate generally to the field of data processing, and moreparticularly to video encoding and decoding. The following describedexemplary embodiments provide a system, method and computer program to,among other things, encode and decode video data based on spatialdisplacement vectors. Therefore, some embodiments have the capacity toimprove the field of computing by allowing for improved video codingbased on the use of both spatial neighboring and non-neighboring blocksto a current block in video data.

As previously described, block based compensation from a differentpicture is also known as motion compensation. Similarly, a blockcompensation can also be done from a previously reconstructed areawithin the same picture. This is referred as intra picture blockcompensation, current picture referencing (CPR for short), or intrablock copy (IBC for short). However, currently in VVC, the search rangeof CPR mode is constrained to be within the current CTU. The effectivememory requirement to store reference samples for CPR mode is 1 CTU sizeof samples. Considering the existing reference sample memory to storereconstructed samples in current 64×64 region, 3 more 64×64 sizedreference sample memory are required. It may be advantageous, therefore,to extends the effective search range of the CPR mode to some part ofthe left CTU while the total memory requirement for storing referencepixels are kept unchanged.

Aspects are described herein with reference to flowchart illustrationsand/or block diagrams of methods, apparatus (systems), and computerreadable media according to the various embodiments. It will beunderstood that each block of the flowchart illustrations and/or blockdiagrams, and combinations of blocks in the flowchart illustrationsand/or block diagrams, can be implemented by computer readable programinstructions.

The following described exemplary embodiments provide a system, methodand computer program that encodes and decodes video data based onspatial displacement vectors. Referring now to FIG. 1, a functionalblock diagram of a networked computer environment illustrating a videocoding system 100 (hereinafter “system”) for encoding and decoding videodata based on spatial displacement vectors. It should be appreciatedthat FIG. 1 provides only an illustration of one implementation and doesnot imply any limitations with regard to the environments in whichdifferent embodiments may be implemented. Many modifications to thedepicted environments may be made based on design and implementationrequirements.

The system 100 may include a computer 102 and a server computer 114. Thecomputer 102 may communicate with the server computer 114 via acommunication network 110 (hereinafter “network”). The computer 102 mayinclude a processor 104 and a software program 108 that is stored on adata storage device 106 and is enabled to interface with a user andcommunicate with the server computer 114. As will be discussed belowwith reference to FIG. 4 the computer 102 may include internalcomponents 800A and external components 900A, respectively, and theserver computer 114 may include internal components 800B and externalcomponents 900B, respectively. The computer 102 may be, for example, amobile device, a telephone, a personal digital assistant, a netbook, alaptop computer, a tablet computer, a desktop computer, or any type ofcomputing devices capable of running a program, accessing a network, andaccessing a database.

The server computer 114 may also operate in a cloud computing servicemodel, such as Software as a Service (SaaS), Platform as a Service(PaaS), or Infrastructure as a Service (IaaS), as discussed below withrespect to FIGS. 5 and 6. The server computer 114 may also be located ina cloud computing deployment model, such as a private cloud, communitycloud, public cloud, or hybrid cloud.

The server computer 114, which may be used for video coding is enabledto run a Video Coding Program 116 (hereinafter “program”) that mayinteract with a database 112. The Video Coding Program method isexplained in more detail below with respect to FIG. 3. In oneembodiment, the computer 102 may operate as an input device including auser interface while the program 116 may run primarily on servercomputer 114. In an alternative embodiment, the program 116 may runprimarily on one or more computers 102 while the server computer 114 maybe used for processing and storage of data used by the program 116. Itshould be noted that the program 116 may be a standalone program or maybe integrated into a larger video coding program.

It should be noted, however, that processing for the program 116 may, insome instances be shared amongst the computers 102 and the servercomputers 114 in any ratio. In another embodiment, the program 116 mayoperate on more than one computer, server computer, or some combinationof computers and server computers, for example, a plurality of computers102 communicating across the network 110 with a single server computer114. In another embodiment, for example, the program 116 may operate ona plurality of server computers 114 communicating across the network 110with a plurality of client computers. Alternatively, the program mayoperate on a network server communicating across the network with aserver and a plurality of client computers.

The network 110 may include wired connections, wireless connections,fiber optic connections, or some combination thereof. In general, thenetwork 110 can be any combination of connections and protocols thatwill support communications between the computer 102 and the servercomputer 114. The network 110 may include various types of networks,such as, for example, a local area network (LAN), a wide area network(WAN) such as the Internet, a telecommunication network such as thePublic Switched Telephone Network (PSTN), a wireless network, a publicswitched network, a satellite network, a cellular network (e.g., a fifthgeneration (5G) network, a long-term evolution (LTE) network, a thirdgeneration (3G) network, a code division multiple access (CDMA) network,etc.), a public land mobile network (PLMN), a metropolitan area network(MAN), a private network, an ad hoc network, an intranet, a fiberoptic-based network, or the like, and/or a combination of these or othertypes of networks.

The number and arrangement of devices and networks shown in FIG. 1 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 1. Furthermore, two or more devices shown in FIG. 1 may beimplemented within a single device, or a single device shown in FIG. 1may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) of system100 may perform one or more functions described as being performed byanother set of devices of system 100.

Referring now to FIG. 2A, a block diagram depicting intra block copy ina picture 200A is depicted. The picture 200A may include a current block202A, a reference block 202B, and a block vector BV. The block vector VBmay be a displacement vector that may indicate an offset between thecurrent block 202A and the reference block 202B. Different from a motionvector in motion compensation, which can be at any value (positive ornegative, at either x or y direction), the block vector BV has a fewconstraints such that it is ensured that the pointed reference block202B is available and already reconstructed. Also, for parallelprocessing consideration, some reference area that is tile boundary orwavefront ladder shape boundary is also excluded.

The coding of a block vector could be either explicit or implicit. Inthe explicit mode (or referred as AMVP mode in inter coding), thedifference between a block vector and its predictor is signaled in theimplicit mode, the block vector is recovered purely from its predictor,in a similar way as a motion vector in merge mode. The resolution of ablock vector, in some implementations, is restricted to integerpositions; in other systems, it may be allowed to point to fractionalpositions

The use of intra block copy at block level, can be signaled using ablock level flag, refer as an IBC flag. In one embodiment, this flag issignaled when the current block 202A is not coded in merge mode. Or itcan be signaled by a reference index approach. This is done by treatingthe current decoded picture as a reference picture. In HEVC SCC, such areference picture is put in the last position of the list. This specialreference picture is also managed together with other temporal referencepictures in the DPB.

There are also some variations for intra block copy, such as treatingthe intra block copy as a third mode, which is different from eitherintra or inter prediction mode. By doing this, the block vectorprediction in merge mode and AMVP mode are separated from regular intermode. For example, a separate merge candidate list is defined for intrablock copy mode, where all the entries in the list are all blockvectors. Similarly, the block vector prediction list in intra block copyAMVP mode only consists of block vectors. The general rules applied toboth lists are: they may follow the same logic as inter merge candidatelist or AMVP predictor list in terms of candidate derivation process.For example, the 5 spatial neighboring locations in HEVC or VVC intermerge mode are accessed for intra block copy to derive its own mergecandidate list.

Referring now to FIG. 2B, a block diagram 200B of intra blockcompensation with a one coding tree unit (CTU) search range is depicted.The search may progress through stages 204A-D. Currently in VVC, thesearch range of CPR mode is constrained to be within the current CTU.The effective memory requirement to store reference samples for CPR modeis 1 CTU size of samples. Considering the existing reference samplememory to store reconstructed samples in current 64×64 region C, 3 more64×64 sized reference samples S may be used. Accordingly, the effectivesearch range of the CPR mode may be extended to some part of the leftCTU while the total memory requirement for storing reference pixels arekept unchanged (1 CTU size, 4 64×64 reference sample memory in total).The bitstream conformance conditions that a valid block vector (mvL, in1/16-pel resolution) should follow are listed as follows. For example,the luma motion vector mvL may obey one or more constraints.

A1: When the derivation process for block availability as specified inthe neighbouring blocks availability checking process is invoked withthe current luma location (xCurr, yCurr) set equal to (xCb, yCb) and theneighbouring luma location (xCb+(mvL[0]>>4), yCb+(mvL[1]>>4)) as inputs,and the output shall be equal to TRUE.

A2: When the derivation process for block availability as specified inthe neighbouring blocks availability checking process is invoked withthe current luma location (xCurr, yCurr) set equal to (xCb, yCb) and theneighbouring luma location (xCb+(mvL[0]>>4)+cbWidth−1,yCb+(mvL[1]>>4)+cbHeight−1) as inputs, and the output shall be equal toTRUE.

B1: One or both the following conditions shall be true. The value of(mvL[0]>>4)+cbWidth is less than or equal to 0. The value of(mvL[1]>>4)+cbHeight is less than or equal to 0.

C1: The following conditions shall be true:

(yCb+(mvL[1]>>4))>>CtbLog2SizeY=yCb>>CtbLog2SizeY(yCb+(mvL[1]>>4)+cbHeight−1)>>CtbLog2SizeY=yCb>>CtbLog2SizeY(xCb+(mvL[0]>>4))>>CtbLog2SizeY>=(xCb>>CtbLog2SizeY)−1(xCb+(mvL[0]>>4)+cbWidth−1)>>CtbLog2SizeY<=(xCb>>CtbLog2SizeY)

C2: When (xCb+(mvL[0]>>4))>>CtbLog2SizeY is equal to(xCb>>CtbLog2SizeY)−1, the derivation process for block availability asspecified in the neighbouring blocks availability checking process isinvoked with the current luma location(xCurr, yCurr) set equal to (xCb,yCb) and the neighbouring luma location(((xCb+(mvL[0]>>4)+CtbSizeY)>>(CtbLog2SizeY−1))<<(CtbLog2SizeY—1),((yCb+(mvL[1]>>4))>>(CtbLog2SizeY—1))<<(CtbLog2SizeY—1)) as inputs, andthe output shall be equal to FALSE.

Referring now to FIG. 2C, a block diagram 200C of HEVC/VVC spatial mergecandidates is depicted. The five spatial merge candidates for HEVC andVVC may include A0, A1, B0, B1, and B2. The order of forming a candidatelist from these positions may be A0->B0->B1->A1->B2.

History-based MVP (HMVP) merge candidates are added to merge list afterthe spatial MVP and TMVP. In this method, the motion information of apreviously coded block is stored in a table and used as MVP for thecurrent CU. The table with multiple HMVP candidates is maintained duringthe encoding/decoding process. The table is reset (emptied) when a newCTU row is encountered. Whenever there is a non-subblock inter-coded CU,the associated motion information is added to the last entry of thetable as a new HMVP candidate.

In VTM3 the HMVP table size S is set to be 6, which indicates up to 6History-based MVP (HMVP) candidates may be added to the table. Wheninserting a new motion candidate to the table, a constrainedfirst-in-first-out (FIFO) rule is utilized wherein redundancy check isfirstly applied to find whether there is an identical HMVP in the table.If found, the identical HMVP is removed from the table and all the HMVPcandidates afterwards are moved forward.

HMVP candidates could be used in the merge candidate list constructionprocess. The latest several HMVP candidates in the table are checked inorder and inserted to the candidate list after the TMVP candidate.Redundancy check is applied on the HMVP candidates to the spatial ortemporal merge candidate.

To reduce the number of redundancy check operations, one or moresimplifications are introduced. A number of HMVP candidates is used formerge list generation is set as (N<=4) ? M: (8−/V), wherein N indicatesnumber of existing candidates in the merge list and M indicates numberof available HMVP candidates in the table. Once the total number ofavailable merge candidates reaches the maximally allowed mergecandidates minus 1, the merge candidate list construction process fromHMVP is terminated.

When intra block copy operates as a separate mode from inter mode, aseparate history buffer, referred as HBVP, will be used for storingpreviously coded intra block copy block vectors.

As a separate mode from inter prediction, it is desirable to have asimplified block vector derivation process for intra block copy mode. Asimilar history-based block vector predictor buffer can be used toperform BV prediction. In the following, some information is providedfor some specific usage of such a HBVP.

A HBVP buffer is established to record the previously IBC coded blocks'BV information, including some other side information such as blocksize, block location, etc.

Based on the recorded information, for each current block, BVs in theHBVP that meet the following conditions are classified intocorresponding categories:

Class 0: The area of coded block (width*height) is greater than or equalto the threshold (64 pixels);Class 1: The frequency of the BV is greater than or equal to 2;Class 2: The coded block coordinates (upper left corner) are to the leftof the current block;Class 3: The coded block coordinates (upper left corner) are above thecurrent block;Class 4: The coded block coordinates (upper left corner) are at theupper left side of the current block;Class 5: The coded block coordinates (upper left corner) are at the topright side of the current block;Class 6: The coded block coordinates (upper left corner) are at thebottom left side of the current block.

For each category, the BV of the most recently coded block is derived asthe BV predictor candidate. A CBVP list is constructed by appending theBV predictor of each category in the order from 0 to 6.

A coded block may be divided into several continuous strings, each ofwhich is followed by the next string along a scan order. The scan ordercan be raster scan or traverse scan. For each string, an string offsetvector (SV) and the length of the string are signalled. The SV is usedto indicate where the reference string is from in the reference area.The length is used to indicate how long the current/reference string is.If a sample in the current block cannot find its match in the referencearea, an escape sample is signaled, and its value is coded directly.

Referring now to FIG. 2D, a block diagram 200D of spatial blocks isdepicted. The spatial blocks may include spatial neighboring blocksA0-E0 and spatial non-adjacent blocks A1-E1, A2-E2, and A3-E3. Vectorprediction includes both block vector prediction for IBC mode and SVprediction for string matching mode, and the prediction can refer toskip mode, direct/merge mode or vector prediction with differencecoding. Spatial neighboring blocks A0-E0 may refer to already codedblocks that are next to a current block. The other positions along thetop row or left column to the current block may also be considered asspatial neighboring positions. Spatial non-neighboring blocks A1-E1,A2-E2, and A3-E3, on the contrary, refer to the previously coded blocksthat are not spatial neighboring blocks (those can be found along thetop row or left column to the current block).

According to one or more embodiments, a coded BV or SV in spatialneighboring or spatial non-neighboring blocks may be used to predict acurrent block coded in IBC mode. In one embodiment, only spatialnon-neighboring blocks coded either in IBC mode or string matching modeare considered as candidates to predict the BV of the current blockcoded in IBC mode. In another embodiment, only spatial non-neighboringblocks coded in IBC mode are considered as candidates to predict the BVof the current block coded in IBC mode. Both spatial neighboring blocksand spatial non-neighboring blocks coded in string matching mode areconsidered as candidates to predict the BV of the current block coded inIBC mode.

According to one or more embodiments, a coded BV or SV in spatialneighboring or spatial non-neighboring blocks may be used to predict acurrent block coded in string matching mode. In one embodiment, onlyspatial non-neighboring blocks coded either in IBC mode or stringmatching mode are considered as candidate to predict the SV of thecurrent block coded in string matching mode. In another embodiment,spatial neighboring blocks coded either in IBC mode or string matchingmode are considered as candidates to predict the SV of the current blockcoded in string matching mode. In another embodiment, both BV and SV inspatial neighboring blocks and spatial non-neighboring blocks codedeither in IBC mode or string matching mode are considered as candidatesto predict the SV of the current block coded in string matching mode.

According to one or more embodiments, the above-discussed spatialcandidates for BV or SV prediction can be put in front of ahistory-based BV or SV candidates in a BV or SV predictor list. Or, theabove-discussed spatial candidates for BV or SV prediction can be putafter a history-based BV or SV candidates in a BV or SV predictor list.When class based prediction is used, as is mentioned in the Introductionpart, putting a spatial neighboring or non-neighboring block into thelist may require the associated location and size information with thecandidates. With the information, a new spatial candidate may be able toput into the right class of predictors. Therefore, the information isalso needed for storing each of spatial neighboring or spatialnon-neighboring blocks, in addition to the BV or SV information.

According to one or more embodiments, when putting several spatialcandidates into a prediction list, some order is followed to access thedesignated spatial locations. For example, to predict an SV in stringmatching mode with only spatial non-neighboring blocks are considered.Then locations A1, B1, C1, D1, E1 may be accessed in order. If one ofthe blocks is coded in either IBC or string matching mode. The vector(either BV or SV) associated with the block may be used to predict theSV in the current block. Similar examples can be derived for predictiona BV in IBC coded current block.

Referring now to FIG. 3, an operational flowchart illustrating the stepsof a method 300 carried out by a program that encodes and decodes videodata based on spatial displacement vectors is depicted.

At 302, the method 300 may include receiving video data including one ormore blocks.

At 304, the method 300 may include predicting a displacement vector of acurrent block coded in intra block copy mode or string matching modefrom among the one or more blocks based on a coded block vector or astring offset vector corresponding to one or more spatial neighboring ornon-neighboring blocks from among the one or more blocks.

At 306, the method 300 may include decoding the video data based on thepredicted displacement vector of the current block.

It may be appreciated that FIG. 3 provides only an illustration of oneimplementation and does not imply any limitations with regard to howdifferent embodiments may be implemented. Many modifications to thedepicted environments may be made based on design and implementationrequirements.

FIG. 4 is a block diagram 400 of internal and external components ofcomputers depicted in FIG. 1 in accordance with an illustrativeembodiment. It should be appreciated that FIG. 4 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environments may be madebased on design and implementation requirements.

Computer 102 (FIG. 1) and server computer 114 (FIG. 1) may includerespective sets of internal components 800A,B and external components900A,B illustrated in FIG. 5. Each of the sets of internal components800 include one or more processors 820, one or more computer-readableRAMs 822 and one or more computer-readable ROMs 824 on one or more buses826, one or more operating systems 828, and one or morecomputer-readable tangible storage devices 830.

Processor 820 is implemented in hardware, firmware, or a combination ofhardware and software. Processor 820 is a central processing unit (CPU),a graphics processing unit (GPU), an accelerated processing unit (APU),a microprocessor, a microcontroller, a digital signal processor (DSP), afield-programmable gate array (FPGA), an application-specific integratedcircuit (ASIC), or another type of processing component. In someimplementations, processor 820 includes one or more processors capableof being programmed to perform a function. Bus 826 includes a componentthat permits communication among the internal components 800A,B.

The one or more operating systems 828, the software program 108 (FIG. 1)and the Video Coding Program 116 (FIG. 1) on server computer 114(FIG. 1) are stored on one or more of the respective computer-readabletangible storage devices 830 for execution by one or more of therespective processors 820 via one or more of the respective RAMs 822(which typically include cache memory). In the embodiment illustrated inFIG. 4, each of the computer-readable tangible storage devices 830 is amagnetic disk storage device of an internal hard drive. Alternatively,each of the computer-readable tangible storage devices 830 is asemiconductor storage device such as ROM 824, EPROM, flash memory, anoptical disk, a magneto-optic disk, a solid state disk, a compact disc(CD), a digital versatile disc (DVD), a floppy disk, a cartridge, amagnetic tape, and/or another type of non-transitory computer-readabletangible storage device that can store a computer program and digitalinformation.

Each set of internal components 800A,B also includes a R/W drive orinterface 832 to read from and write to one or more portablecomputer-readable tangible storage devices 936 such as a CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk orsemiconductor storage device. A software program, such as the softwareprogram 108 (FIG. 1) and the Video Coding Program 116 (FIG. 1) can bestored on one or more of the respective portable computer-readabletangible storage devices 936, read via the respective R/W drive orinterface 832 and loaded into the respective hard drive 830.

Each set of internal components 800A,B also includes network adapters orinterfaces 836 such as a TCP/IP adapter cards; wireless Wi-Fi interfacecards; or 3G, 4G, or 5G wireless interface cards or other wired orwireless communication links. The software program 108 (FIG. 1) and theVideo Coding Program 116 (FIG. 1) on the server computer 114 (FIG. 1)can be downloaded to the computer 102 (FIG. 1) and server computer 114from an external computer via a network (for example, the Internet, alocal area network or other, wide area network) and respective networkadapters or interfaces 836. From the network adapters or interfaces 836,the software program 108 and the Video Coding Program 116 on the servercomputer 114 are loaded into the respective hard drive 830. The networkmay comprise copper wires, optical fibers, wireless transmission,routers, firewalls, switches, gateway computers and/or edge servers.

Each of the sets of external components 900A,B can include a computerdisplay monitor 920, a keyboard 930, and a computer mouse 934. Externalcomponents 900A,B can also include touch screens, virtual keyboards,touch pads, pointing devices, and other human interface devices. Each ofthe sets of internal components 800A,B also includes device drivers 840to interface to computer display monitor 920, keyboard 930 and computermouse 934. The device drivers 840, R/W drive or interface 832 andnetwork adapter or interface 836 comprise hardware and software (storedin storage device 830 and/or ROM 824).

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,some embodiments are capable of being implemented in conjunction withany other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring to FIG. 5, illustrative cloud computing environment 500 isdepicted. As shown, cloud computing environment 500 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Cloud computingnodes 10 may communicate with one another. They may be grouped (notshown) physically or virtually, in one or more networks, such asPrivate, Community, Public, or Hybrid clouds as described hereinabove,or a combination thereof. This allows cloud computing environment 500 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 5 are intended to be illustrative only and that cloud computingnodes 10 and cloud computing environment 500 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring to FIG. 6, a set of functional abstraction layers 600 providedby cloud computing environment 500 (FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments are notlimited thereto. As depicted, the following layers and correspondingfunctions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and Video Coding 96. Video Coding 96 mayencode and decode video data based on spatial displacement vectors.

Some embodiments may relate to a system, a method, and/or a computerreadable medium at any possible technical detail level of integration.The computer readable medium may include a computer-readablenon-transitory storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outoperations.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program code/instructions for carrying out operationsmay be assembler instructions, instruction-set-architecture (ISA)instructions, machine instructions, machine dependent instructions,microcode, firmware instructions, state-setting data, configuration datafor integrated circuitry, or either source code or object code writtenin any combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. The computer readable programinstructions may execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) may execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects or operations.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer readable media according to variousembodiments. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, or portion of instructions,which comprises one or more executable instructions for implementing thespecified logical function(s). The method, computer system, and computerreadable medium may include additional blocks, fewer blocks, differentblocks, or differently arranged blocks than those depicted in theFigures. In some alternative implementations, the functions noted in theblocks may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed concurrently orsubstantially concurrently, or the blocks may sometimes be executed inthe reverse order, depending upon the functionality involved. It willalso be noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwaremay be designed to implement the systems and/or methods based on thedescription herein.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

The descriptions of the various aspects and embodiments have beenpresented for purposes of illustration, but are not intended to beexhaustive or limited to the embodiments disclosed. Even thoughcombinations of features are recited in the claims and/or disclosed inthe specification, these combinations are not intended to limit thedisclosure of possible implementations. In fact, many of these featuresmay be combined in ways not specifically recited in the claims and/ordisclosed in the specification. Although each dependent claim listedbelow may directly depend on only one claim, the disclosure of possibleimplementations includes each dependent claim in combination with everyother claim in the claim set. Many modifications and variations will beapparent to those of ordinary skill in the art without departing fromthe scope of the described embodiments. The terminology used herein waschosen to best explain the principles of the embodiments, the practicalapplication or technical improvement over technologies found in themarketplace, or to enable others of ordinary skill in the art tounderstand the embodiments disclosed herein.

What is claimed is:
 1. A method of video coding, executable by aprocessor, comprising: receiving video data including one or moreblocks; predicting a displacement vector of a current block coded inintra block copy mode or string matching mode from among the one or moreblocks based on a coded block vector or a string offset vectorcorresponding to one or more spatial neighboring or non-neighboringblocks from among the one or more blocks; and decoding the video databased on the predicted displacement vector of the current block.
 2. Themethod of claim 1, wherein only spatial non-neighboring blocks coded inintra block copy mode or string matching mode are considered ascandidates to predict the block vector of the current block coded inintra block copy mode.
 3. The method of claim 1, wherein only spatialnon-neighboring blocks coded in intra block copy mode are considered ascandidates to predict the block vector of the current block coded inintra block copy mode.
 4. The method of claim 1, wherein both spatialneighboring blocks and spatial non-neighboring blocks coded in stringmatching mode are considered as candidates to predict the block vectorof the current block coded in intra block copy mode.
 5. The method ofclaim 1, wherein the coded block vector or a string offset vector in thespatial neighboring or the spatial non-neighboring blocks is used topredict a current block coded in string matching mode from among the oneor more blocks.
 6. The method of claim 5, wherein only spatialnon-neighboring blocks coded either in intra block copy mode or stringmatching mode are considered as candidates to predict the string offsetvector of the current block coded in string matching mode.
 7. The methodof claim 5, wherein spatial neighboring blocks coded in intra block copymode or string matching mode are considered as candidates to predict thestring offset vector of the current block coded in string matching mode.8. The method of claim 5, wherein both block vector and string offsetvector in spatial neighboring blocks and spatial non-neighboring blockscoded either in intra block copy mode or string matching mode areconsidered as candidates to predict the string offset vector of thecurrent block coded in string matching mode.
 9. The method of claim 1,wherein spatial candidates for predicting the block vector or the stringoffset vector are based on a history-based block vector or string offsetvector candidates in a block vector or string offset vector predictorlist.
 10. The method of claim 9, wherein based on a class-basedprediction being used, a spatial neighboring or non-neighboring block,location information, and size information are added to the predictorlist.
 11. A computer system for video coding, the computer systemcomprising: one or more computer-readable non-transitory storage mediaconfigured to store computer program code; and one or more computerprocessors configured to access said computer program code and operateas instructed by said computer program code, said computer program codeincluding: receiving code configured to cause the one or more computerprocessors to receive video data including one or more blocks;predicting code configured to cause the one or more computer processorsto predict a displacement vector of a current block coded in intra blockcopy mode or string matching mode from among the one or more blocksbased on a coded block vector or a string offset vector corresponding toone or more spatial neighboring or non-neighboring blocks from among theone or more blocks; and decoding code configured to cause the one ormore computer processors to decode the video data based on the predicteddisplacement vector of the current block.
 12. The computer system ofclaim 11, wherein only spatial non-neighboring blocks coded in intrablock copy mode or string matching mode are considered as candidates topredict the block vector of the current block coded in intra block copymode.
 13. The computer system of claim 11, wherein only spatialnon-neighboring blocks coded in intra block copy mode are considered ascandidates to predict the block vector of the current block coded inintra block copy mode.
 14. The computer system of claim 13, wherein bothspatial neighboring blocks and spatial non-neighboring blocks coded instring matching mode are considered as candidates to predict the blockvector of the current block coded in intra block copy mode.
 15. Thecomputer system of claim 11, wherein the coded block vector or a stringoffset vector in the spatial neighboring or the spatial non-neighboringblocks is used to predict a current block coded in string matching modefrom among the one or more blocks.
 16. The computer system of claim 15,wherein only spatial non-neighboring blocks coded either in intra blockcopy mode or string matching mode are considered as candidates topredict the string offset vector of the current block coded in stringmatching mode.
 17. The computer system of claim 15, wherein spatialneighboring blocks coded in intra block copy mode or string matchingmode are considered as candidates to predict the string offset vector ofthe current block coded in string matching mode.
 18. The computer systemof claim 15, wherein both block vector and string offset vector inspatial neighboring blocks and spatial non-neighboring blocks codedeither in intra block copy mode or string matching mode are consideredas candidates to predict the string offset vector of the current blockcoded in string matching mode.
 19. The computer system of claim 11,wherein spatial candidates for the block vector or a string offsetvector are based on a history-based block vector or string offset vectorcandidates in a block vector or string offset vector predictor list. 20.A non-transitory computer readable medium having stored thereon acomputer program for video coding, the computer program configured tocause one or more computer processors to: receive video data includingone or more blocks; predict a current block coded in intra block copymode from among the one or more blocks based on a coded block vector orstring offset vector corresponding to one or more spatial neighboring ornon-neighboring blocks from among the one or more blocks; and decode thevideo data based on the predicted current block.